Scholarlink

<p>This paper proposes a Distributed Hierarchical Triggered Model Predictive Control (DHTMPC) framework to enhance the cyber–physical resilience of AC microgrids operating under adverse weather conditions and communication uncertainties. The proposed architecture integrates distributed tube-based model predictive control, event-triggered communication, and topology-aware predictive optimization within a multi-layer hierarchical structure. A hybrid energy storage system (HESS), composed of battery energy storage and supercapacitor units, is optimally coordinated to provide fast dynamic frequency regulation and economic power dispatch. Communication delays, packet loss, renewable intermittency, and network reconfiguration constraints are explicitly modeled within a unified robust optimization framework. An invariant tube mechanism guarantees constraint satisfaction under bounded disturbances and degraded communication channels. The proposed approach is validated on an IEEE 33-bus microgrid under load variations, communication delays up to 1&#xa0;s, renewable intermittency, grid faults, and 20% packet loss. The results demonstrate a 10.75% reduction in operating cost, frequency deviation maintained within ± 0.05&#xa0;Hz, settling time below 10&#xa0;s under severe delays, and successful voltage recovery after fault conditions, confirming the robustness and scalability of the proposed framework.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An Improved Resiliency of AC Microgrid with Distributed Hierarchical Triggered Model Predictive Control Using Hybrid Energy Storage Under Adverse Weather Conditions

  • 期刊论文

  • 发表日期：

    2026年4月16日

查看全文
  • Deepak Kumar,
  • Anil Kumar

摘要

This paper proposes a Distributed Hierarchical Triggered Model Predictive Control (DHTMPC) framework to enhance the cyber–physical resilience of AC microgrids operating under adverse weather conditions and communication uncertainties. The proposed architecture integrates distributed tube-based model predictive control, event-triggered communication, and topology-aware predictive optimization within a multi-layer hierarchical structure. A hybrid energy storage system (HESS), composed of battery energy storage and supercapacitor units, is optimally coordinated to provide fast dynamic frequency regulation and economic power dispatch. Communication delays, packet loss, renewable intermittency, and network reconfiguration constraints are explicitly modeled within a unified robust optimization framework. An invariant tube mechanism guarantees constraint satisfaction under bounded disturbances and degraded communication channels. The proposed approach is validated on an IEEE 33-bus microgrid under load variations, communication delays up to 1 s, renewable intermittency, grid faults, and 20% packet loss. The results demonstrate a 10.75% reduction in operating cost, frequency deviation maintained within ± 0.05 Hz, settling time below 10 s under severe delays, and successful voltage recovery after fault conditions, confirming the robustness and scalability of the proposed framework.